Multimodal Neuroimaging Training Program
NIRS module
Anna Manelis
Department of Psychology, CNBC
Carnegie Mellon University
Faculty Instructor: Theodore Huppert, PhD
Technical Adviser: Nancy Beluk
July 14, 2011
NIRS
•
•
•
•
•
portable
relatively non-invasive
low cost
has low sensitivity to subjects’ motion
able to measure both oxy- hemoglobin and
deoxy- hemoglobin as a function of nearinfrared wavelengths
CW6 system
Registration
Find a right spot
sources
detectors
4 experiments
• Median nerve stimulation (2 subjects)
• Finger tapping (1 subject)
• Words encoding and recognition (1
subject)
• Working memory (2 subjects)
the measurements were taken at two
wavelengths (690nm and 830nm).
Finger tapping
15s on + 15s off
QuickTime™ and a
decompressor
are needed to see this picture.
5 blocks
Right hand
Unilateral probe
Finger tapping
detectors
detectors
sources
Finger tapping
Left motor cortex
0
50
100
150
Raw data
200
0
50
100
150
200
ΔOD – changes in optical
Density at 830 nm
Optical density = -log (I1/I0)
Finger tapping
Left motor cortex
0
hp=70s, GF=2s
50
100
150
200
Finger tapping
Left motor cortex
0
hp=70s, GF=2s
50
100
150
200
Finger tapping
Left motor cortex
0
hp=70s, GF=2s
50
100
150
200
Memory Studies
Right
Verbal recognition
memory
encoding
690nm
830nm
0
50
100
150
time (sec)
200
0
50
100
150
time (sec)
200
Verbal recognition
memory
encoding
0 10 20 30 40 50 60 70 80
0 10 20 30 40 50 60 70
time (sec)
time (sec)
HbR
HbO
HbT
N-back predictions
fMRI results
Owen et al., 2005 (HBM)
N-back load effect
3-back
2-back
1-back
0
10
20
30
40
50
time (sec)
60
70
Summary
NIRS can detect changes in brain activity in
various tasks that include simple sensorymotor and higher cognitive functions tasks
Limitations
Three types of noise in NIRS data:
• instrument noise
- sometimes difficult to detect
- not much support from the companies
- may have different distribution across channels
and wavelengths
• physiological noise
• experiment error
- cap motion (especially problematic for bilateral
caps)
- cap placement
690 nm vs. 830 nm
690 nm
830 nm
Noise in the data
Limitations
Three types of noise in NIRS data:
• instrument noise
- sometimes difficult to detect
- not much support from the companies
- may have different distribution across channels
and wavelengths
• physiological noise
• experiment error
- cap motion (especially problematic for bilateral
caps)
- cap placement
Limitations
Methods for data analysis and registration are not well
developed (i.e., work in progress)
NIRS is sensitive to
•
the changes in the scalp thickness over time
•
between-subject variability within the brain
stuctures
Acknowledgements
Seong-Gi Kim, PhD
Bill Eddy, PhD
Theodore Huppert, PhD
Nancy Beluk
Tomika Cohen
MNTP Faculty, Staff, and Teaching Assistants
University of Pittsburgh Medical Center
Carnegie Mellon Center for Neural Basis of Cognition
NIH R90DA02342
5T32-MH019983-12
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